Matlabgetstart

MATLABxct经典仿真程序设计源码MATLABxct classic simulation programming source code(MATLABxct classic simulation programming source MATLABxct classic simulation programming source code)

第二代Contourlet工具包，处理去噪，压缩，分割效果很好，是应用的热点。Matlab语言的(Contourlet Kit second generation, processing denoising, compression, segmentation works well, is the application of the hot spots. Matlab language)

说明：  k-means算法完整源代码！！数据都已给，(k-means algorithm full source code! ! Data are given,)

solar battery system simulation

基于灰色关联理论，用于计算个因素与决策变量之间的灰色关联度(Calculation of grey relational degree)

通过VB调用MATLAB实现图形和界面的结合(MATLAB realize through the VB calls the combination of graphics and interface)

该演示中包含的代码演示如何氡相似的功能，可以用来提高（以及部分）在Connectome电磁图像单元格边界。 请举出下列文件如果您发现此代码有用： Ritwik库马尔，阿梅里奥五雷纳和Hanspeter Pfister说“氡样的特点及其应用Connectomics”，接受，IEEE计算机学会研讨会在生物医学图像分析（MMBIA）2010年数学方法 http://seas.harvard.edu/〜 rkkumar radonLikeFeaturesDemo.m：演示边缘增强用氡相似的功能， getEdgeFeatures.m：助手为高斯函数的二阶导数滤波器 makeBarFilters.m：助手为高斯函数的二阶导数滤波器 sample.png：示例图像在此演示使用(The demo included in the code demonstrates how Radon-Like Features can be used to enhance (and segment) cell boundaries in Connectome EM images. Please cite the following paper if you find this code useful: Ritwik Kumar, Amelio V. Reina & Hanspeter Pfister, “Radon-Like Features and their Application to Connectomics”, accepted, IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA) 2010 http://seas.harvard.edu/~rkkumar radonLikeFeaturesDemo.m : Demonstrates edge enhancement using Radon-Like Features getEdgeFeatures.m : Helper function for Gaussian Second Derivative Filters makeBarFilters.m : Helper function for Gaussian Second Derivative Filters sample.png : Sample image for use in this demo )

ocr optical character recognition

各种滤波器的设计，包括高斯低通滤波器。hilberrt带通滤波器，插值滤波器等等。(Various filter design, including Gaussian low-pass filter. hilberrt band-pass filter, the interpolation filter and so on.)

数学建模的教学培训文件，matlab 软件应用培训(Mathematical modeling of teaching and training files, Matlab software application training)